Multi-UAV Surveillance over Forested Regions

Abstract

S-UAVs (Small-Unmanned Aerial Vehicles) have emerged as low-cost alternatives for aerial surveillance over forests. However, they provide limited coverage owing to their low altitudes and short endurance. Therefore, a quick and effective surveillance necessitates optimal flying paths, maximizing ground visibility. Even though the occlusion of ground points due to vegetation is significant in forests, it is generally neglected. This paper proposes a probabilistic sensing model that incorporates both occlusions due to terrain and vegetation, in the visibility computations and presents a two-step approach to determine near-optimal flight paths: (a) waypoints are strategically deployed to enhance visibility, using centroidal Voronoi tessellation, and (b) flyable paths are designed using a clustered spiral-alternating algorithm. Simulation studies conducted on synthetic terrains and a reconstructed terrain, from satellite data of tree-cover and a Digital Elevation Model (DEM), show the effectiveness of the proposed method in improving the terrain visibility as compared to commonly used grid-based waypoints.